An integrated metagenomic, metabolomic and transcriptomic survey of Populus across genotypes and environments

Bridging molecular information to ecosystem-level processes would provide the capacity to understand system vulnerability and, potentially, a means for assessing ecosystem health. Here, we present an integrated dataset containing environmental and metagenomic information from plant-associated microbial communities, plant transcriptomics, plant and soil metabolomics, and soil chemistry and activity characterization measurements derived from the model tree species Populus trichocarpa. Soil, rhizosphere, root endosphere, and leaf samples were collected from 27 different P. trichocarpa genotypes grown in two different environments leading to an integrated dataset of 318 metagenomes, 98 plant transcriptomes, and 314 metabolomic profiles that are supported by diverse soil measurements. This expansive dataset will provide insights into causal linkages that relate genomic features and molecular level events to system-level properties and their environmental influences.

Using Raman Spectroscopy and SERS for in-situ studies of rhizosphere bacteria

Bacteria colonize plant roots to form a symbiotic relationship with the plant and can play in important role in promoting plant growth. Raman spectroscopy is a useful technique to study these bacterial systems and the chemical signals they utilize to interact with the plant. We present a Raman study of Pantoea YR343 that was isolated from the rhizosphere of Populus deltoides (Eastern Cottonwood). Pantoea sp. YR343 produce yellowish carotenoid pigment that play a role in protection against UV radiation, in the anti-oxidative pathways and in membrane fluidity. Raman spectroscopy is used to non-invasively characterize the membrane bound carotenoids. The spectra collected from a mutant strain created by knocking out the crtB gene that encodes a phytoene synthase responsible for early stage of carotenoid biosynthesis, lack the carotenoid peaks. Surface Enhanced Raman Spectroscopy is being employed to detect the plant phytoharmone indoleacetic acid that is synthesized by the bacteria. This work describes our recent progress towards utilizing Raman spectroscopy as a label free, non-destructive method of studying plant-bacteria interactions in the rhizosphere.

Bacterial immobilization for imaging by atomic force microscopy

AFM is a high-resolution (nm scale) imaging tool that mechanically probes a surface. It has the ability to image cells and biomolecules, in a liquid environment, without the need to chemically treat the sample. In order to accomplish this goal, the sample must sufficiently adhere to the mounting surface to prevent removal by forces exerted by the scanning AFM cantilever tip. In many instances, successful imaging depends on immobilization of the sample to the mounting surface. Optimally, immobilization should be minimally invasive to the sample such that metabolic processes and functional attributes are not compromised. By coating freshly cleaved mica surfaces with porcine (pig) gelatin, negatively charged bacteria can be immobilized on the surface and imaged in liquid by AFM. Immobilization of bacterial cells on gelatin-coated mica is most likely due to electrostatic interaction between the negatively charged bacteria and the positively charged gelatin. Several factors can interfere with bacterial immobilization, including chemical constituents of the liquid in which the bacteria are suspended, the incubation time of the bacteria on the gelatin coated mica, surface characteristics of the bacterial strain and the medium in which the bacteria are imaged. Overall, the use of gelatin-coated mica is found to be generally applicable for imaging microbial cells.

Automated Image Analysis of Fluorescence Microscopic Images to Identify Protein-protein Interactions

The identification of protein-protein interactions along with their spatial and temporal localization is vital data for assigning functional information to proteins. Historically, these data sets obtained from fluorescence microscopy, have been analyzed manually, a process that is both time consuming and tedious. The development of an automated system that can measure the location dynamics of the interaction between two proteins inside a live cell is a high priority. This paper describes an automated image analysis system used to identify the interactions between two proteins of interest fused to either GFP or DIV IVA, a bacterial cell division protein that localizes to the cell poles [1]. Upon the induction of DIV IVA fusion protein expression, the GFP-fusion protein will be recruited to the cell poles if a positive interaction occurs. Advanced image processing and feature extraction algorithms are discussed in detail and a statistical feature set used to quantify the image-based information is developed.

Automated Image Analysis of Fluorescence Microscopic Images to Identify Protein-protein Interactions

The identification of protein-protein interactions along with their spatial and temporal localization is vital data for assigning functional information to proteins. Historically, these data sets obtained from fluorescence microscopy, have been analyzed manually, a process that is both time consuming and tedious. The development of an automated system that can measure the location dynamics of the interaction between two proteins inside a live cell is a high priority. This paper describes an automated image analysis system used to identify the interactions between two proteins of interest fused to either GFP or DIV IVA, a bacterial cell division protein that localizes to the cell poles [1]. Upon the induction of DIV IVA fusion protein expression, the GFP-fusion protein will be recruited to the cell poles if a positive interaction occurs. Advanced image processing and feature extraction algorithms are discussed in detail and a statistical feature set used to quantify the image-based information is developed.

Global molecular and morphological effects of 24-hour chromium(VI) exposure on Shewanella oneidensis MR-1

The biological impact of 24-h ("chronic") chromium(VI) [Cr(VI) or chromate] exposure on Shewanella oneidensis MR-1 was assessed by analyzing cellular morphology as well as genome-wide differential gene and protein expression profiles. Cells challenged aerobically with an initial chromate concentration of 0.3 mM in complex growth medium were compared to untreated control cells grown in the absence of chromate. At the 24-h time point at which cells were harvested for transcriptome and proteome analyses, no residual Cr(VI) was detected in the culture supernatant, thus suggesting the complete uptake and/or reduction of this metal by cells. In contrast to the untreated control cells, Cr(VI)-exposed cells formed apparently aseptate, nonmotile filaments that tended to aggregate. Transcriptome profiling and mass spectrometry-based proteomic characterization revealed that the principal molecular response to 24-h Cr(VI) exposure was the induction of prophage-related genes and their encoded products as well as a number of functionally undefined hypothetical genes that were located within the integrated phage regions of the MR-1 genome. In addition, genes with annotated functions in DNA metabolism, cell division, biosynthesis and degradation of the murein (peptidoglycan) sacculus, membrane response, and general environmental stress protection were upregulated, while genes encoding chemotaxis, motility, and transport/binding proteins were largely repressed under conditions of 24-h chromate treatment.